Brain wave power in Epilepsy: A power spectral EEG analysis

Objectives: Continuous connected breathing (CCB) is a high-frequency breathing technique without breath retention. This study examines changes in electroencephalogram (EEG) band power and heart rate variability (HRV) before, during and after breathwork intervention of 3 rounds of 40 CCB versus normal breathing in healthy volunteers. Materials and Methods: Thirty-three healthy volunteers, aged between 19 and 23 years, participated in the study (n = 15; female = 7; mean age = 21.5 years) group, while the control group consisted of 18 individuals (n = 18; male = 11; mean age = 19.6 years). After acquiring baseline measures, the study group engaged in 40 CCB practice online for 10 days, while the control group continued with their usual activities. EEG and HRV signals were recorded for both groups after the 10 days. Post-intervention, the study group practised 40 CCB breathwork, while the control group breathed normally during signal acquisition. EEG was recorded for 1-min durations at five different time events (1st, 4th, 5th, 7th and 10th min) according to the protocol. HRV was continuously recorded for the entire 10 min, and 1-min readings corresponding to the EEG recording time intervals were analysed. EEG signals were acquired using an Enobio-8 cap with dry electrodes in pre-frontal (FP1 and FP2), temporal (T7 and T8), central (C3 and C4) and occipital (O1 and O2) regions. HRV data were acquired from Polar H7/H10 chest strap sensors through Bluetooth using Elite HRV app on android phone and data were later processed with Kubios software. EEG signals were processed using MATLAB software to extract EEG power for delta (0– 3.5Hz), theta (4–7 Hz), alpha (8–13 Hz), beta (14–29 Hz) and gamma frequencies (30–50 Hz). The EEG power and HRV signals were later arranged as before-after and during time events and statistically analysed for within and between-group changes using t-tests for significance of means. Results: There was an overall quantitative change in EEG band power of −2 units within the study group and −0.03 within the control group. A significant decrease was found in overall delta (−2.27), theta (−1.7), alpha (−1.8) and beta (−2.27) brain waves in pre-frontal (FP1, FP8), temporal (T7, T8) and occipital (O1, O2) regions after breathwork compared to before within the study group. A significant increase was found in beta (+2.8) band power in the control group with a higher increase in the left compared to the right hemisphere. Bilateral average change ranged from −1.6 to −2.6 in the study and −0.1 to +4.9 in the control group. HRV parameters were reduced after intervention in both groups but without significance. The parameters improved after the intervention compared to during within the study group, though not significant. Conclusion: 10 days of practice of 40 CCB breathworks (3 rounds) for 5 min/day may reduce EEG power in delta, theta, alpha and beta waves. It may help to maintain autonomic balance with an increase of HRV in the recovery phase after an initial decrease during breathwork. Further studies are recommended to test the consistency of outcomes.

Background: Changes in low frequency waves and altered psychological status were associated with epilepsy. Epilepsy can cause anxiety and depression and many other complications and anti-seizure medication can make the patients lethargic, tired and drowsy.Objective: To assess and quantify cortical brain waves in female patients with epilepsy by power spectral analysis of signals of quantitative electroencephalogram(QEEG). Methods: This study was carried out on 20 female patients with epilepsy aged 20-40 years and 20 healthy female volunteer of similar age were control. EEG was recorded from 22 scalp electrodes in different region all over the head by an EEG data acquisition device, EEG Traveler Brain Tech 32+ CMEEG-01, India in all participants. Power spectral analysis of EEG data was done with Brain Tech 40+ Standard version 4.47a analysis software by calculating relative band power of delta, theta, alpha and beta brainwaves to assess cortical electrical activity. Data were expressed as mean ± SD. For statistical analysis, Independent-Samples t test was used. The P value ≤ 0.05 was considered as statistical significance. Results: Mean values of relative power of delta and theta were significantly higher and values of alpha and beta were significantly lower in all cortical areas of epilepsy patients compared to control. Conclusion: It may be concluded that higher low frequency brain wave and lower high frequency brain wave were associated with epilepsy. J Bangladesh Soc Physiol 2025;20(1): 1-9

Introductions: Medical students are required to lifelong learning. Electroencephalog-raphy is a neuroscience tool that can be used to record brain wave activity related to a person's cognitive function. Objective: This study was conducted to see the relationship between self-regulated learning and cognitive function with quantitative electroencepha-logram (qEEG) parameters. Methods: This study used an observa-tional analytic approach to assess self-regulated learning and cog-nitive function using the MSLQ and MoCA-INA questionnaires. qEEG recording to see brain wave activity was done when the eyes were open and closed and seen in alpha and beta waves. The sam-ple of this study amounted to 32 respondents who were willing to carry out each research procedure. Results: The study findings reveal a significant correlation between SRL and qEEG parameters. In the open-eye condition, such a correla-tion exists in the frontal and central regions with regard to alpha waves (P = 0.046 and P = 0.047). In contrast, in the closed-eye condition, it exists in the occipital, central, and parietal regions with alpha waves (P = 0.005, P = 0.021, and P = 0.049) and the central region with beta waves (P = 0.030). There is a significant correla-tion between cognitive function and qEEG parameters observed in both open and closed-eye conditions within the frontal region beta waves (P = 0.024, P = 0.044, and P = 0.021). Conclusions: There is a relationship between SRL and cognitive function with alpha and beta wave activity on qEEG recording.

Human attachments shape interbrain synchrony toward efficient performance of social goals

A better understanding of the network responses of cortical activities during rest and cognitive tasks is necessary. Therefore, in this study, we aimed to evaluate cerebral activities during attentional tasks by using mobile electroencephalography, identifying the types of attentional components and brain waves. In this experimental study, we enrolled 12 healthy young adults. The attentional tasks comprised parts A and B of the Trail-Making Test (TMT). Nineteen electroencephalography electrodes were placed over various brain regions. The Wilcoxon signed-rank test was used to examine the differences in power levels between the rest and TMT conditions. During TMT part A, the electroencephalography power level of the delta waves was significantly higher in the right frontal, left central, left occipital, left inferior frontal, right mid-temporal, right posterior temporal, and middle parietal areas (P < .05) than those during the resting state; that of the alpha waves was significantly lower in the left posterior temporal area (P = .006); and that of the high gamma waves was significantly lower in the left parietal (P = .05) and left occipital (P = .002) areas. During TMT part B, the electroencephalography power level of the beta waves was significantly higher in the right frontal area (P = .041) than that during the resting state, and that of the low gamma waves was significantly higher in the left frontal pole, right frontal, and right inferior frontal areas (P < .05). During the focused attentional task, the power level of the delta waves increased and that of the alpha waves decreased, and during the alternating attentional task, those of both the beta and gamma waves increased. The delta waves were related to the whole brain, the alpha and high gamma waves to the left posterior lobe, and the beta and low gamma waves to both frontal lobes. These findings contribute to the basic knowledge necessary to develop new attentional assessment methods for clinical situations.

BackgroundHighly structured electroencephalography (EEG) oscillations can occur in adults during etomidate-induced general anesthesia, but the link between these two phenomena is poorly understood. Therefore, in the present study, we investigated the electroencephalogram dynamics of etomidate-induced loss of consciousness (LOC) in order to understand the neurological mechanism of etomidate-induced LOC.MethodsThis study is a prospective observational study. Etomidate-induced anesthesia was performed on eligible patients undergoing elective surgery. We analyzed EEG data from 20 patients who received etomidate for the induction of general anesthesia. We used power spectra and coherence methods to process and analyze the EEG data. Our study was based on 4-channel EEG recordings.ResultsCompared with the baseline (awake period), etomidate induced an increase in power in delta, theta, alpha and beta waves during LOC. Compared with the awake period, the delta-wave (1–4 Hz), alpha-wave(8–13 Hz), and theta-wave(4–8 Hz) coherence increased significantly during LOC, while the slow-wave (< 1 Hz) coherence decreased. However, the delta wave (1.0–4.0 Hz) during etomidate-induced LOC was more coherent than during the awake period (1.86–3.17 Hz, two-group test for coherence, p < 0.001).ConclusionsThe neural circuit mechanism of etomidate-induced LOC is closely related to the induction of oscillation in delta, theta, alpha and beta waves and the enhancement of delta-wave coherence.Trial registrationChiCTR1800017110

Background. The method of anterior decompression (discectomy) for monosegmental stenosis of the cervical spinal canal is subjectively assessed as highly effective by both neurosurgeons and the vast majority of patients. However, the objective criteria for the early effectiveness of this intervention have not been sufficiently studied to date. Aim of the study to evaluate the dynamics of electroencephalography parameters in the preoperative and early postoperative period in patients with monosegmental stenosis of the cervical spine. Materials and methods. Electroencephalography studies were conducted on 22 patients of the neurosurgery department, before and after surgical treatment under code A16.23.085.001. The spectral composition of the bioelectrical activity of the brain (alpha, beta, delta and theta rhythms), as well as the coherence of oscillations in selected leads, were studied. Results. In the preoperative period, a disorganized type of electroencephalogramm was recorded in the examined group according to the classification of E.A. Zhirmunskaya; there was a decrease in the index and amplitude of the alpha rhythm in the parietal-occipital leads; predominance of high-amplitude beta activity in the frontal-central leads; presence of diffuse delta activity of the average index and theta activity of the average index, localized in leads P3, P4, C3, C4. On the 5th day after the operation, an organized type of electroencephalography was recorded on the encephalogram; a well-modulated alpha rhythm was observed, with a frequency in the range from 9 to 10 Hz, and an amplitude of 70 to 80 microvolts. Low-amplitude beta rhythm activity was recorded in the frontocentral leads. Low-amplitude delta and theta rhythms were recorded in the parieto-occipital leads and had a low index. Overall, the obtained data indicated positive dynamics in the restoration of cortical rhythms. Conclusion. The positive dynamics of cerebral cortex biorhythms in the early postoperative period allows the use of the electroencephalography method to objectify the results of surgical treatment, and in the future for the purposes of neurorehabilitation.

This study aims to analyze the relationship between brainwave activity and the learning readiness of students with disabilities by utilizing EEG (Electroencephalography) signals. EEG signals are used to detect the brain's electrical activity that reflects mental states, including focus, concentration, and readiness to receive learning. This study was conducted at SLB 'Aisyiyah Krian with a quantitative approach through EEG signal measurement before and during the learning process. The results showed a significant correlation between the dominance of alpha and beta waves with learning readiness, while the dominance of theta and delta waves indicated unpreparedness. These findings provide a foundation for the development of a more inclusive, objective, and adaptive neurotechnology-based learning approach for students with disabilities.

Electroencephalographic study of parasomnia: Sleep-talking, enuresis and bruxism

Electroencephalogram (EEG) signal has been studied as a biological signal input for human-computer interaction. This research defines a control signal - focus value R to measure the concentration degree of human brain. According to frequency band, human brain waves have been classified to, such as alpha wave, beta wave, theta wave, delta wave. The focus value R is the ratio of beta wave's and theta wave's total power on frequency domain. The research then attests to the reasonable representing of brain concentration with R. To conclude, the research utilizes the self-controlled brain concentration degrees (the levels an individual can pay attention) into a human-computer interface application (HCI) like music control, which can be used for the disabled like Parkinson's disease patients to change music volume and switch as they like.

The goal of this study was to determine whether the cortical responses elicited by whole‐body balance perturbations were similar to established cortical markers of action monitoring. Postural changes imposed by balance perturbations elicit a robust negative potential (N1) and a brisk increase of theta activity in the electroencephalogram recorded over midfrontal scalp areas. Because action monitoring is a cognitive function proposed to detect errors and initiate corrective adjustments, we hypothesized that the possible cortical markers of action monitoring during balance control (N1 potential and theta rhythm) scale with perturbation intensity and the eventual execution of reactive stepping responses (as opposed to feet‐in‐place responses). We recorded high‐density electroencephalogram from eleven young individuals, who participated in an experimental balance assessment. The participants were asked to recover balance following anteroposterior translations of the support surface at various intensities, while attempting to maintain both feet in place. We estimated source‐resolved cortical activity using independent component analysis. Combining time‐frequency decomposition and group‐level general linear modeling of single‐trial responses, we found a significant relation of the interaction between perturbation intensity and stepping responses with multiple cortical features from the midfrontal cortex, including the N1 potential, and theta, alpha, and beta rhythms. Our findings suggest that the cortical responses to balance perturbations index the magnitude of a deviation from a stable postural state to predict the need for reactive stepping responses. We propose that the cortical control of balance may involve cognitive control mechanisms (i.e., action monitoring) that facilitate postural adjustments to maintain postural stability.

To assess spatial working memory disorders in patients with mild depressive disorders and determine their neurophysiological correlates. Thirty patients (right-handed) with ICD-10 diagnosis Mood Disorders (F31.3, F32.0, F33.0, F34.1), aged 37±8 years, were examined before treatment. A control group included 30 mentally and somatically healthy individuals (32±7 years old). The study of spatial working memory was carried out using the Corsi Block-Tapping test. EEG was recorded and the values of the spectral power of theta, alpha and beta rhythms were analyzed. A decrease in the level of working memory that was correlated with higher values of theta rhythm power in the frontal and occipital regions and alpha rhythm in the frontal cortex was observed in affective disorders with mild depressive symptoms.

In this study cyclic changes of human sleep structure were examined. For whole-night polysomnograms of 35 healthy volunteers of both sexes, manual hypnograms were created and divided into NREM-REM cycles. EEG signals from C3-A2 derivation were analysed by computer using a Fast Fourier Transform (FFT). For consecutive NREM-REM cycles of individual sleep stages, EEG power density contents for delta, theta, alpha, sigma and beta waves were analysed. For consecutive sleep cycles, a clear decrease in NREM sleep duration, especially slow wave sleep duration, was obtained. In addition, a decrease in power density of delta waves was observed. For consecutive sleep cycles, increases in REM sleep duration and in power density of theta and alpha waves were obtained. In consecutive sleep cycles, high amplitude delta slow waves are replaced by higher frequency and lower amplitude waves. Thus stages of NREM sleep are replaced by stages of REM.

Background: This study explores the captivating query about how olfactory stimulation affects neural activity, particularly examining changes in the absolute and relative power of lower frequency waves (delta and theta across various brain regions). This investigation employs Quantitative Electroencephalogram (QEEG) to analyze the effects of exposure to the aroma of lemongrass (Cymbopogon Citratus) essential oil. Aim: To evaluate the impact of inhaling lemongrass (Cymbopogon Citratus) essential oil aroma on EEG patterns in awake healthy female adults, employing power spectral analysis. Materials and Method: In this self-controlled experiment, 30 healthy adult female participants were exposed to the water mist as control and after taking baseline recording, they inhaled aromatic mist from room air, and again brain activities were recorded using QEEG. Data was collected from scalp electrodes readings and outcomes from before and after exposure to the aroma were compared. This analysis was strengthened by comparing the results between exposure to water mist and oil mist employing the Wilcoxon Matched-Pairs Signed Rank Test. Results: Significant elevation of absolute and relative power of theta in prefrontal region (p=0.002; p=0.000) along with rise of delta and theta absolute power in frontal area (p=0.000; p=0.000) was observed. Conclusion: This study sheds light onto the background oscillatory fluctuations in lower frequency bands that may indicate more relaxed state of brain activity due to inhalation of lemongrass essential oil. J Med Coll Women Hosp.2024; 20 (1):16-22

Classification of resting and cognitive states has its importance in brain neuroscience for understating the underlying behaviors of cognition. The human brain is considered as a complex system having different mental states such as resting, active or cognitive states. It is a well-understood fact that the brain activity increases with the increased demand of cognition. The deep learning algorithm based on Pre-trained convolutional neural network (CNN) networks have been used as a transfer learning for the classification of rest and cognitive states and also assessed the cognitive load using brain waves particularly alpha wave. EEG data were collected from 34 human participants at resting and during a learning state. The important EEG electrodes were selected based on the effective connectivity method and after preprocessing, EEG data has been segmented into equal number of segments using selected electrodes to investigate the deep temporal information for cognitive load assessment. The brain waves were extracted using discrete wavelet transform (DWT) for each segment and fed these segments to proposed model for classification and assessment of cognitive load. The results shows that alpha brain wave produced consistent behavior using for all cognition tasks based on pre-trained CNN models for classification and cognitive load assessment.